root-cause-analysis

root-cause-analysis is a skill for Claude Code, Codex from microsoft/cat-agent-skills. It costs 139 tokens per session (1,389 once invoked), scanned A, original, MIT.

A structured method for finding the underlying cause of a failure rather than stopping at its visible symptoms. It records the problem, traces the chain of contributing facts, and can use methods such as 5 Whys and a Fishbone diagram.

In plain words
What is it for?
Use it to investigate why something failed, distinguish symptoms from causes, and document a root-cause analysis.
Why use it?
It reduces guesswork during incidents, defects, and post-mortems. Reaching a fixable underlying cause makes it more likely that the same problem will not happen again.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit Use it to investigate why something failed, distinguish symptoms from causes, and document a root-cause analysis.

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Install with agentmods
npx agentmods add skills/microsoft/cat-agent-skills/root-cause-analysis
About the project

microsoft/cat-agent-skills is a static website that catalogs reusable instruction sets and related packages for AI agents. People use it to search, filter, rate, and download skills for Cowork, Copilot Studio, and Scout, along with Copilot plugins and Scout automations. The catalogue entries are the skills, instructions, plugins, and settings displayed by the site.

microsoft/cat-agent-skills · 93 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add microsoft/cat-agent-skills --skill root-cause-analysis
Clone the repo
git clone --depth 1 https://github.com/microsoft/cat-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for root-cause-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/root-cause-analysis/github.svg)](https://agentmods.dev/skills/microsoft/cat-agent-skills/root-cause-analysis)
Your own site
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/root-cause-analysis"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/root-cause-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for root-cause-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/root-cause-analysis"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/root-cause-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,389 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00139 $0.01389
Opus 5.5 $0.00056 $0.00556
Sonnet 5.5 $0.00028 $0.00278
Haiku 4.5 $0.00014 $0.00139

Measured 1mo ago against content hash 588629718903, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

root-cause-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

submissions/root-cause-analysis/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Root Cause Analysis

Guide the user through structured problem diagnosis to move from observed symptoms to the true underlying cause, using repeatable techniques that prevent guessing or stopping at surface-level fixes.

Instructions

  1. Lock the problem statement

    • State the exact symptom or failure in one sentence.
    • Capture when it occurred, where, and who or what was affected.
    • Do not allow vague wording like "it broke" or "performance is bad."
  2. Map the symptom chain

    • List every observed symptom as a fact, not a hypothesis.
    • For each symptom, ask: "What could produce this?"
    • Keep asking "why" at least three levels deep before proposing any cause.
  3. Apply 5 Whys

    • Start from the problem statement.
    • Ask "why" repeatedly, recording each answer.
    • Stop when you reach a cause that, if fixed, would prevent the symptom from recurring.
    • If you reach a cause that is a contributing factor rather than a fixable origin, keep going.
    • Load references/rca-methods.md if the problem is complex or the user asks for a specific technique.
  4. Build a Fishbone diagram

    • Categorize potential causes across: People, Process, Technology, Data, Environment, Management.
    • For each category, list specific contributing factors backed by evidence the user can confirm.
    • Do not invent facts; if a factor is uncertain, mark it as unverified.
    • Use assets/fishbone-template.html to structure the diagram. Open the template, replace the placeholder text in each category branch with the contributing factors identified above, and return the filled-in HTML so the user can save and open it.
    • Do NOT build a new diagram from scratch. Do NOT generate matplotlib, code-generated plots, or any output that is not based on the provided template. Editing and returning the provided HTML template is the correct output.
    • Also replace the PROBLEM STATEMENT placeholder at the top of the template with the locked problem statement from step 1. Verify that no template placeholder or default text remains before returning the file.
    • Classify every factor as CONFIRMED, UNVERIFIED, or DISPROVEN using the rules in the Evidence classification section below. In particular: only facts stated verbatim or by direct paraphrase in the user's input may be CONFIRMED. If a claim is built on the absence of information — for example, inferring a missing control because no one mentioned it — it must be UNVERIFIED, not CONFIRMED.
    • Render every factor with its status tag using this exact markup: <span class="tag tag-{status-lowercase}">{STATUS}</span> {factor text}. For example: <span class="tag tag-confirmed">CONFIRMED</span> Config file was missing at deploy time. The visible label must be uppercase CONFIRMED, UNVERIFIED, or DISPROVEN, but the class suffix must be lowercase confirmed, unverified, or disproven to match the template CSS.
    • Escape all user-derived text before inserting it into the HTML. Replace & with &amp;, < with &lt;, > with &gt;, " with &quot;, and ' with &#039;. The only raw markup allowed in the output is the fixed status <span> described above; all problem-statement and factor text must be HTML-escaped.

Read the full file on GitHub · 77 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 77 lines · 139 tokens per session scan A 588629718903

Subscribe to this mod's changes

root-cause-analysis is a skill published in the GitHub repository microsoft/cat-agent-skills (93 stars, last pushed today), licensed MIT. It adds 139 tokens to every session and 1,389 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.

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